Computer Science

The Future of Software Engineering Has Arrived.AI can now write code, generate tests, analyze requirements, explain systems, assist with debugging, and automate increasingly complex engineering tasks.But building great software has never been just about writing code.How do you design the right architecture?How do you build systems that remain secure and reliable at scale?How do you integrate AI without sacrificing quality, privacy, or control?How do you use AI to make engineers more effective without replacing engineering judgment?Engineering Software Systems in the AI Era explores these questions and provides a practical framework for designing, building, testing, securing, deploying, operating, and evolving modern software systems.Inside, you will explore:Modern software architecture and system designCloud-native and scalable systemsData architecture and intelligent data systemsAI engineering and AI-native applicationsCybersecurity and privacy by designSoftware quality and reliabilityDevOps, DevSecOps, and continuous deliveryObservability and production engineeringAI-augmented software developmentAI agents and intelligent engineering workflowsPlatform engineeringTechnical debt and engineering strategyAI governance and risk managementTechnical leadership in the AI eraThe future of software engineeringThe central message is simple:AI may make software development faster. Engineering makes software better.Learn how to combine the power of artificial intelligence with the discipline of software engineering to build systems that are secure, scalable, reliable, intelligent, maintainable, and ready for the future.

Your AI assistant forgets you every time the session ends. Building Persistent AI shows you how to fix that — by moving memory, personality, and identity out of the model and into a file you own and control.

What if you could build software without manually writing every line of code? Artificial Intelligence is transforming the way software is designed, developed, tested, and deployed.But becoming an AI-powered software engineer isn't simply about asking an AI to write code.It's about learning how to think, design, build, test, verify, and improve software with AI as your engineering partner.The AI-Powered Software Engineer takes you on a practical journey from traditional programming to AI-assisted development and modern AI engineering.Learn how to use AI to:Design software. Generate and understand code. Debug complex problems. Build AI-powered applications. Automate workflows. Test and secure software. Deploy real products. Build AI-powered SaaS businesses.You don't need to become the fastest programmer in the room.You need to become the person who can turn an idea into a working, reliable, valuable system.Write less code. Think more. Build faster. Engineer smarter.The future of software engineering isn't humans versus AI.It's humans building with AI.

A practical implementation framework covering 22 essential data center operational domains. Assess gaps, establish priorities and build a controlled improvement roadmap.

Go beyond writing code and learn what it takes to build software that lasts. Fundamentals of Software Engineering walks you through requirements, architecture, testing, deployment and production using practical trade-offs and a real-world case study. Follow TaskFlow from its first requirement to a system built to scale, evolve and survive the real world.

Statistics is the language of uncertainty. AI is the science of learning from data. Together, they provide a powerful foundation for modern intelligent systems.Applied Statistics with AI: Hypothesis Testing and Inference for Modern Models is designed for learners who want to understand how statistical methods can be applied to Artificial Intelligence, Machine Learning, Data Science, and modern research.The book begins with essential statistical foundations, including data types, sampling, preprocessing, descriptive statistics, visualization, probability, and probability distributions. It then builds toward statistical inference, covering estimation, Maximum Likelihood Estimation, Bayesian estimation, hypothesis testing, p-values, confidence intervals, Type I and Type II errors, and statistical significance.Readers will learn how classical statistical tests such as t-tests, ANOVA, and Chi-Square tests can be used in AI-related contexts, along with non-parametric methods such as Wilcoxon, Mann-Whitney, Kruskal-Wallis, and Kolmogorov-Smirnov tests.The book then connects statistics directly to Machine Learning through regression, model evaluation, cross-validation, resampling, feature selection, PCA, regularization, A/B testing, and statistical power.Advanced chapters explore Bayesian inference, MCMC, causal inference, uncertainty quantification in deep learning, and confidence estimation in AI predictions. Real-world case studies demonstrate how statistical inference can support applications in healthcare, finance, Natural Language Processing, and Computer Vision.The book also addresses an increasingly important dimension of AI: responsible statistical practice. Readers will explore bias detection, fairness, ethical hypothesis testing, and the responsible interpretation of AI research results.Finally, the book looks ahead to automated statistical inference, AI-driven hypothesis generation, and emerging research challenges.Whether you are a student learning statistics for AI, a researcher evaluating machine learning experiments, a data scientist analyzing evidence, or an AI practitioner seeking stronger statistical foundations, this book provides a structured path from fundamental concepts to modern applications.Understand the data. Test the hypothesis. Quantify uncertainty. Make better AI decisions.

Learn how to create, design, and integrate game audio and music using Unity and FMOD, from sound effects and ambience to interactive audio systems and dynamic music. Includes a complete video game project to put your knowledge into practice.

Stop wasting engineering hours on manual Jira maintenance. Learn how to combine deterministic Jira governance with targeted Atlassian Rovo AI agents to build a self-triage, friction-free delivery engine.

Move Beyond Simple Prompts. Build Reliable, Autonomous AI Systems.Connecting an LLM to an API is easy; building an AI agent that works reliably in production is hard. Mastering AI Agents gives you the exact architectural frameworks, workflows, and engineering practices needed to design, deploy, and scale intelligent agents that solve real-world problems.Practical Engineering: Master memory systems, tool integration, multi-agent orchestration, and system security.Production-Ready Focus: Learn how to evaluate, monitor, and maintain agents so they remain controllable and safe.Evergreen Principles: Built on core software architecture principles that stay valuable even as frameworks and models evolve.Grab your copy today and start building the next generation of intelligent software!

Short Description of the BookSecuring Modern AI Applications is a practical guide to securing LLM-powered applications, RAG systems, AI agents, and modern AI development environments.The book explains AI-specific threats such as prompt injection, data leakage, RAG poisoning, insecure tool use, agent abuse, and AI supply-chain risks while also covering traditional application security, privacy, governance, secure development, monitoring, testing, and red teaming.Designed for developers, AI engineers, cybersecurity professionals, architects, and technology leaders, the book focuses on practical principles that remain useful as AI technologies continue to evolve.Build AI. Secure AI. Govern AI.

Artificial Intelligence is no longer the future—it is transforming the way we work, learn, create, and innovate today. Whether you're a student, professional, entrepreneur, freelancer, educator, or software developer, understanding Generative AI is becoming an essential skill.Generative AI Mastery is your practical guide to unlocking the full potential of AI. From mastering prompt engineering and boosting productivity to enhancing business operations, software development, research, writing, creativity, and decision-making, this book provides the knowledge and real-world strategies you need to use AI with confidence.Inside, you'll discover:How Generative AI works and why it mattersEffective prompt engineering techniquesPractical AI applications for work, business, and educationAI tools for writing, coding, research, and creativityEthical AI, privacy, security, and responsible useFuture career opportunities in the age of AIPractical prompts, templates, and implementation strategiesRather than focusing on a single AI tool, this book teaches timeless principles and transferable skills that remain valuable as AI continues to evolve.Whether you're just beginning your AI journey or looking to maximize your professional potential, Generative AI Mastery will help you work smarter, innovate faster, and thrive in the age of Artificial Intelligence.

Explore the foundations and future of modern computing—from artificial intelligence and distributed systems to cybersecurity, quantum technologies, and responsible computing. Modern Computer Science connects essential concepts with emerging technologies, real-world applications, and the challenges shaping the future of the discipline.

Descubre cómo crear, diseñar e integrar música, efectos, ambientes y diálogos en videojuegos con Unity y FMOD, y ponlo en práctica con un videojuego real completo.

Scheme looks simple by design, but beneath its tiny core lies a remarkably powerful way of thinking about programs. Essential Scheme takes you from your first expression to continuations, macros and interpreters, revealing the ideas behind the language along the way. Clear examples and careful explanations make Scheme’s deepest concepts approachable.

This Developer's Guide is the second in the "Disciples of Renown™" gaming series. It leads you through the development of the "Sanctify Hollowed Grounds" Role-Playing Game in both Construct v3 & v2 encoding formats. It's perfect for novices, experienced web developers, and anyone wanting their own bespoke game, artwork, and features.